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    <meta name="description" content="分割+多路归并我们可以将一个很大的文件，切分成很多个小文件，使得每个小文件能够单独的装进内存，并将每个小文件进行内排序（快速排序等等），然后再将多个小文件进行多路归并排序，最终得到一个有序的文件。 多路归并排序在大数据领域也是常用的算法，常用于海量数据排序。当数据量特别大时，这些数据无法被单个机器内存容纳，它需要被切分位多个集合分别由不同的机器进行内存排序（map过程），然后再进行多路归并算法将来">
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          大文件排序
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        <h1 id="分割-多路归并"><a href="#分割-多路归并" class="headerlink" title="分割+多路归并"></a>分割+多路归并</h1><p>我们可以将一个很大的文件，切分成很多个小文件，使得每个小文件能够单独的装进内存，并将每个小文件进行内排序（快速排序等等），然后再将多个小文件进行多路归并排序，最终得到一个有序的文件。</p>
<p>多路归并排序在大数据领域也是常用的算法，常用于海量数据排序。当数据量特别大时，这些数据无法被单个机器内存容纳，它需要被切分位多个集合分别由不同的机器进行内存排序（map过程），然后再进行多路归并算法将来自多个不同机器的数据进行排序（reduce 过程），这是流式多路归并排序。</p>
<p>多路归并排序的优势在于内存消耗极低，它的内存占用和输入文件的数量成正比，和数据总量无关，数据总量只会线性正比影响排序的时间。</p>
<p><img src="/2022/03/20/%E5%A4%A7%E6%96%87%E4%BB%B6%E6%8E%92%E5%BA%8F/Large_File_Sorting.jpg" alt="img"></p>
<h1 id="多路归并的几种方案"><a href="#多路归并的几种方案" class="headerlink" title="多路归并的几种方案"></a>多路归并的几种方案</h1><p>多路归并排序有3种思路，分别是使用堆、胜者树、败者数。</p>
<h2 id="堆"><a href="#堆" class="headerlink" title="堆"></a>堆</h2><p>从 K 个序列中各取一个元素，并记录每个元素的来源数组，建立一个含 K 个元素的小根堆。此时堆顶就是最小的元素，取出堆顶元素，并从堆顶元素的来源序列中取下一个元素放入堆顶，然后向下调整。在向下调整过程中需要和其两个子结点比较，需要比较 2 次。</p>
<h2 id="胜者树"><a href="#胜者树" class="headerlink" title="胜者树"></a>胜者树</h2><p>胜者树在向上调整的时候首先需要获得父结点，然后再获得兄弟结点，然后再比较。比堆少一半的比较次数。</p>
<h2 id="败者树"><a href="#败者树" class="headerlink" title="败者树"></a>败者树</h2><p>败者树在向上调整的时候，只需要获得父结点并比较即可。相较于胜者树，它不必获取兄弟结点了，减小了访存时间。</p>
<h1 id="使用MapReduce解决"><a href="#使用MapReduce解决" class="headerlink" title="使用MapReduce解决"></a>使用MapReduce解决</h1><figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> org.apache.hadoop.fs.FileSystem;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.io.IntWritable;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.io.LongWritable;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.mapreduce.Job;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.conf.Configuration;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.fs.Path;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.io.Text;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.mapreduce.Mapper;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.mapreduce.Reducer;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.mapreduce.lib.input.FileInputFormat;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.mapreduce.lib.input.TextInputFormat;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;</span><br><span class="line"><span class="keyword">import</span> org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;</span><br><span class="line"></span><br><span class="line"><span class="keyword">import</span> java.io.IOException;</span><br><span class="line"><span class="keyword">import</span> java.net.URI;</span><br><span class="line"></span><br><span class="line"><span class="comment">/**</span></span><br><span class="line"><span class="comment"> * <span class="doctag">@author</span>: SongyangJi</span></span><br><span class="line"><span class="comment"> * <span class="doctag">@description</span>:</span></span><br><span class="line"><span class="comment"> * <span class="doctag">@since</span>: 2022/3/20</span></span><br><span class="line"><span class="comment"> */</span></span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="keyword">public</span> <span class="keyword">class</span> <span class="title class_">Sort</span> &#123;</span><br><span class="line"></span><br><span class="line">    <span class="keyword">public</span> <span class="keyword">static</span> <span class="keyword">class</span> <span class="title class_">MyMapper</span> <span class="keyword">extends</span> <span class="title class_">Mapper</span>&lt;LongWritable, Text, IntWritable, IntWritable&gt; &#123;</span><br><span class="line">        <span class="keyword">private</span> <span class="keyword">static</span> <span class="keyword">final</span> <span class="type">IntWritable</span> <span class="variable">data</span> <span class="operator">=</span> <span class="keyword">new</span> <span class="title class_">IntWritable</span>(); <span class="comment">//静态变量了解一下</span></span><br><span class="line"></span><br><span class="line">        <span class="keyword">public</span> <span class="keyword">void</span> <span class="title function_">map</span><span class="params">(LongWritable key, Text value, Context context)</span></span><br><span class="line">                <span class="keyword">throws</span> IOException, InterruptedException &#123;</span><br><span class="line">            <span class="type">String</span> <span class="variable">line</span> <span class="operator">=</span> value.toString();</span><br><span class="line">            data.set(Integer.parseInt(line));</span><br><span class="line">            context.write(data, <span class="keyword">new</span> <span class="title class_">IntWritable</span>(<span class="number">1</span>));</span><br><span class="line">        &#125;</span><br><span class="line">    &#125;</span><br><span class="line"></span><br><span class="line">    <span class="keyword">public</span> <span class="keyword">static</span> <span class="keyword">class</span> <span class="title class_">MyReducer</span> <span class="keyword">extends</span> <span class="title class_">Reducer</span>&lt;IntWritable, IntWritable, IntWritable, Text&gt; &#123;</span><br><span class="line">        <span class="keyword">private</span> <span class="keyword">final</span> <span class="type">Text</span> <span class="variable">word</span> <span class="operator">=</span> <span class="keyword">new</span> <span class="title class_">Text</span>();</span><br><span class="line"></span><br><span class="line">        <span class="keyword">public</span> <span class="keyword">void</span> <span class="title function_">reduce</span><span class="params">(IntWritable key, Iterable&lt;IntWritable&gt; values, Context context)</span></span><br><span class="line">                <span class="keyword">throws</span> IOException, InterruptedException &#123;</span><br><span class="line">            <span class="keyword">for</span> (IntWritable val : values) &#123;</span><br><span class="line">                context.write(key, <span class="keyword">new</span> <span class="title class_">Text</span>());</span><br><span class="line">            &#125;</span><br><span class="line">        &#125;</span><br><span class="line">    &#125;</span><br><span class="line"></span><br><span class="line"></span><br><span class="line">    <span class="keyword">public</span> <span class="keyword">static</span> <span class="keyword">void</span> <span class="title function_">main</span><span class="params">(String[] args)</span> <span class="keyword">throws</span> Exception &#123;</span><br><span class="line">        <span class="type">Configuration</span> <span class="variable">conf</span> <span class="operator">=</span> <span class="keyword">new</span> <span class="title class_">Configuration</span>();</span><br><span class="line">        <span class="type">Job</span> <span class="variable">job</span> <span class="operator">=</span> Job.getInstance(conf, <span class="string">&quot;Sort&quot;</span>);</span><br><span class="line">        <span class="comment">//run jar class 主方法</span></span><br><span class="line">        job.setJarByClass(Sort.class);</span><br><span class="line">        <span class="comment">//设置map</span></span><br><span class="line">        job.setMapperClass(MyMapper.class);</span><br><span class="line">        job.setMapOutputKeyClass(IntWritable.class);</span><br><span class="line">        job.setMapOutputValueClass(IntWritable.class);</span><br><span class="line">        <span class="comment">//设置reduce</span></span><br><span class="line">        job.setReducerClass(MyReducer.class);</span><br><span class="line">        job.setOutputKeyClass(IntWritable.class);</span><br><span class="line">        job.setOutputValueClass(IntWritable.class);</span><br><span class="line">        <span class="comment">//设置input format</span></span><br><span class="line">        job.setInputFormatClass(TextInputFormat.class);</span><br><span class="line">        <span class="comment">//设置output format</span></span><br><span class="line">        job.setOutputFormatClass(TextOutputFormat.class);</span><br><span class="line">        <span class="comment">// 设置输入输出路径</span></span><br><span class="line">        FileInputFormat.addInputPath(job, <span class="keyword">new</span> <span class="title class_">Path</span>(args[<span class="number">0</span>]));</span><br><span class="line">        FileOutputFormat.setOutputPath(job, <span class="keyword">new</span> <span class="title class_">Path</span>(args[<span class="number">1</span>]));</span><br><span class="line">        System.exit(job.waitForCompletion(<span class="literal">true</span>) ? <span class="number">0</span> : <span class="number">1</span>);</span><br><span class="line">    &#125;</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>



<blockquote>
<p>参考</p>
<p><a target="_blank" rel="noopener" href="https://cloud.tencent.com/developer/article/1592913">https://cloud.tencent.com/developer/article/1592913</a></p>
<p><a target="_blank" rel="noopener" href="https://luisstruggle.github.io/blog/Large_File_Sorting.html">https://luisstruggle.github.io/blog/Large_File_Sorting.html</a></p>
</blockquote>

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